Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

Given the importance of ecology and its entry into various fields in general and the urban environment particularly; ecological cities take wide ranges of application at multiple regional and global levels. However, it repeatedly noted that there was a state of cognitive confusion and overlapping in the term ecology comes from the diversity of implementation within several disciplines. Architects, designers, and planners have instilled biological development directly into the formal principles as well as the social structures of the ecological cities. Therefore, the research presents a rapid review of the most relevant areas that dealt with the ecological cities by research and analysis at various levels, from the concept and definition of

Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

  This  Research aim to identify the factors affecting the strategic implementation of sewage projects and to seek to activate the real follow-up of projects to identify the factors that accompany their implementation, The study included a sample of the projects of the investment plan implemented for the Directorate General of sewage in the governorates of Iraq, which was completed during the six years period (2010-2016). The sample of the research was four projects: The project of implementation and processing of the treatment plant and the lifting station and the conveyor line for the project of IMARA/The third stage/Al-Sanaf marshland , The project of the processing and implementation of the treatment plant with the

   يهدف البحث إلى التعرف على The research aims to identify the effect ofاثر التركيب العمري للسكان على الناتج المحلي الإجمالي في العراق وتحديد الفئات العمرية من أطفال ومنتجين أي من هم في سن العمل والمسنين لأهمية ذلك لإغراض التخطيط الاقتصادي.إنeffectofeee age structure of the population on GDP in Iraq and determine the age groups of children and any of the producers wham are of working age and the elderly of the importance for the purposes of economic planning. نسبة الفئة العمرية Proportion of the age group (00- -4 4سنوات اقتربت من

An investigation of the quadrupole deformation of Kr, Sr, Zr, and Mo isotopes has been conducted using the HFB method and SLy4 Skyrme parameterization. The primary role of occupancy of single particle state 2d5/2 in the existence of the weakly bound structure around N=50 is probed. Shell gaps are performed using a few other calculations for the doubly magic number 100Sn using different Skyrme parameterizations. We explore the interplays among neutron pairing strength and neutron density profile in two dimensions, along with the deformations of 100Sn.

In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

Data compression offers an attractive approach to reducing communication costs using available bandwidth effectively. It makes sense to pursue research on developing algorithms that can most effectively use available network. It is also important to consider the security aspect of the data being transmitted is vulnerable to attacks. The basic aim of this work is to develop a module for combining the operation of compression and encryption on the same set of data to perform these two operations simultaneously. This is achieved through embedding encryption into compression algorithms since both cryptographic ciphers and entropy coders bear certain resemblance in the sense of secrecy. First in the secure compression module, the given text is p